There are a number of models and methodologies that are used to compute or evaluate geophysical or petrophysical properties. For example, there is the conventional deterministic model method for evaluating or computing geophysical and petrophysical properties. There is also a Chevron deterministic model implemented by Chevron U.S.A. Inc. This method enhances the conventional deterministic method. There are also the multi-mineral methods (e.g., MULTIMIN deterministic model from Paradigm Ltd or ELAN from Schlumberger Ltd or QUANTIMIN from Techsia SA or MINSOLVE from Senergy Ltd).
The most fundamental differences between the above-mentioned methods are how these methods treat the “volumetrics.” In other words, the main differences between the above three methods lie in the way the various properties relating to rocks or formations in the underground are presented or treated. In general, in all of the above-mentioned methods, a set of volumes describes the underground or subsurface geology (i.e., the formations underground). In that particular set of volumes, all the volumes must sum to 100%, in accordance with the mass conservation principle.
The above three methods describe sand and shale in the rock. However, these three methods differ about what the “elemental” brick constituting the rock is. For example, in the deterministic model “shale” is a rock with substantial amounts of clay and some quartz (which both are minerals forming rocks in the multi-mineral model). In addition, calcite and dolomite (which is a carbonate rock forming mineral) are also handled explicitly. Each method uses a different set of output properties to describe a rock formation. Hence, users of these methods must be able to interpret the output properties according to the method used to obtain the properties.
In some instances, users of different methods will have difficulties relaying to each other the results as each user uses a different set of output properties. This can pose some challenges in communication, as the two users “speak a different language”. Furthermore, a user may also seek to obtain information on the rock formation using two or more different methods, for example to check accuracy of the output properties or results or for quality control purposes. Because, each of the method outputs a different set of output properties, the user must convert a value of one output parameter from one to another manually. This can be tedious and subject to human errors.